Short description and motivation
Autonomous vehicles and vessels increasingly depend on GNSS for positioning and navigation, making them vulnerable to spoofing attacks that manipulate navigation information. Such attacks can cause an autonomous system to deviate from its intended trajectory while remaining difficult to distinguish from normal positioning errors. This thesis will investigate methods for detecting GNSS spoofing by combining GNSS observations with complementary navigation information, such as inertial measurements and vehicle dynamics.
Main objective
The main objective is to design and experimentally evaluate a GNSS spoofing detection approach for autonomous navigation, with particular emphasis on detection of previously unseen and gradually evolving spoofing attacks.
Tasks to be followed for completion
- Review literature on GNSS spoofing, detection methods and secure autonomous navigation.
- Define an autonomous-navigation scenario, threat model, spoofing attacks and evaluation methodology.
- Develop a simulation environment and generate or obtain suitable GNSS and complementary navigation data.
- Implement and experimentally compare selected spoofing-detection approaches under different attack scenarios.
- Analyse and critically discuss detection performance, robustness, limitations and implications.
Suggested references
- Broumandan, A., & Lachapelle, G. (2018). Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation. Sensors.
- Dasgupta, S., Rahman, M., et al. (2022). A Sensor Fusion-Based GNSS Spoofing Attack Detection Framework for Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems.
- Zhou, Z. H., Li, H., et al. (2024). Velocity Consistency Checking Based GNSS Spoofing Detection Method for Vehicles. IEEE Transactions on Vehicular Technology.
- Zhou, Z. H., Li, H., & Lu, M. Q. (2025). Doppler-Based RAIM for GNSS Spoofing Detection in Vehicular Applications. IEEE Transactions on Vehicular Technology.